Pathogenomes and variations in Shiga toxin production among geographically distinct clones of Escherichia coli O113:H21.

Infections with globally disseminated Shiga toxin-producing Escherichia coli (STEC) of the O113:H21 serotype can progress to severe clinical complications, such as hemolytic uremic syndrome (HUS). Two phylogeographically distinct clonal complexes have been established by multi locus sequence typing (MLST). Infections with ST-820 isolates circulating exclusively in Australia have caused severe human disease, such as HUS. Conversely, ST-223 isolates prevalent in the US and outside Australia seem to rarely cause severe human disease but are frequent contaminants. Following a genomic epidemiology approach, we wanted to gain insights into the underlying cause for this disparity. We examined the plasticity in the genome make-up and Shiga toxin production in a collection of 20 ST-820 and ST-223 strains isolated from produce, the bovine reservoir, and clinical cases. STEC are notorious for assembly into fragmented draft sequences when using short-read sequencing technologies due to the extensive and partly homologous phage complement. The application of long-read technology (LRT) sequencing yielded closed reference chromosomes and plasmids for two representative ST-820 and ST-223 strains. The established high-resolution framework, based on whole genome alignments, single nucleotide polymorphism (SNP)-typing and MLST, includes the chromosomes and plasmids of other publicly available O113:H21 sequences and allowed us to refine the phylogeographical boundaries of ST-820 and ST-223 complex isolates and to further identify a historic non-shigatoxigenic strain from Mexico as a quasi-intermediate. Plasmid comparison revealed strong correlations between the strains' featured pO113 plasmid genotypes and chromosomally inferred ST, which suggests coevolution of the chromosome and virulence plasmids. Our pathogenicity assessment revealed statistically significant differences in the Stx2a-production capabilities of ST-820 as compared to ST-223 strains under RecA-induced Stx phage mobilization, a condition that mimics Stx-phage induction. These observations suggest that ST-820 strains may confer an increased pathogenic potential in line with the strain-associated epidemiological metadata. Still, some of the tested ST-223 cultures sourced from contaminated produce or the bovine reservoir also produced Stx at levels comparable to those of ST-820 isolates, which calls for awareness and for continued surveillance of this lineage.

Pathogenomes of Atypical Non-shigatoxigenic Escherichia coli NSF/SF O157:H7/NM: Comprehensive Phylogenomic Analysis Using Closed Genomes.

The toxigenic conversion of Escherichia coli strains by Shiga toxin-converting (Stx) bacteriophages were prominent and recurring events in the stepwise evolution of enterohemorrhagic E. coli (EHEC) O157:H7 from an enteropathogenic (EPEC) O55:H7 ancestor. Atypical, attenuated isolates have been described for both non-sorbitol fermenting (NSF) O157:H7 and SF O157:NM serotypes, which are distinguished by the absence of Stx, the characteristic virulence hallmark of Stx-producing E. coli (STEC). Such atypical isolates either never acquired Stx-phages or may have secondarily lost stx during the course of infection, isolation, or routine subculture; the latter are commonly referred to as LST (Lost Shiga Toxin)-isolates. In this study we analyzed the genomes of 15 NSF O157:H7 and SF O157:NM strains from North America, Europe, and Asia that are characterized by the absence of stx, the virulence hallmark of STEC. The individual genomic basis of the Stx (-) phenotype has remained largely undetermined as the majority of STEC genomes in public genome repositories were generated using short read technology and are in draft stage, posing a major obstacle for the high-resolution whole genome sequence typing (WGST). The application of LRT (long-read technology) sequencing provided us with closed genomes, which proved critical to put the atypical non-shigatoxigenic NSF O157:H7 and SF O157:NM strains into the phylogenomic context of the stepwise evolutionary model. Availability of closed chromosomes for representative Stx (-) NSF O157:H7 and SF O157:NM strains allowed to describe the genomic basis and individual evolutionary trajectories underlying the absence of Stx at high accuracy and resolution. The ability of LRT to recover and accurately assemble plasmids revealed a strong correlation between the strains' featured plasmid genotype and chromosomally inferred clade, which suggests the coevolution of the chromosome and accessory plasmids. The identified ancestral traits in the pSFO157 plasmid of NSF O157:H7 strain LSU-61 provided additional evidence for its intermediate status. Taken together, these observations highlight the utility of LRTs for advancing our understanding of EHEC O157:H7/NM pathogenome evolution. Insights into the genomic and phenotypic plasticity of STEC on a lineage- and genome-wide scale are foundational to improve and inform risk assessment, biosurveillance, and prevention strategies.

A novel subnetwork alignment approach predicts new components of the cell cycle regulatory apparatus in Plasmodium falciparum.

BACKGROUND: According to the World Health organization, half the world's population is at risk of contracting malaria. They estimated that in 2010 there were 219 million cases of malaria, resulting in 660,000 deaths and an enormous economic burden on the countries where malaria is endemic. The adoption of various high-throughput genomics-based techniques by malaria researchers has meant that new avenues to the study of this disease are being explored and new targets for controlling the disease are being developed. Here, we apply a novel neighborhood subnetwork alignment approach to identify the interacting elements that help regulate the cell cycle of the malaria parasite Plasmodium falciparum. RESULTS: Our novel subnetwork alignment approach was used to compare networks in Escherichia coli and P. falciparum. Some 574 P. falciparum proteins were revealed as functional orthologs of known cell cycle proteins in E. coli. Over one third of these predicted functional orthologs were annotated as "conserved Plasmodium proteins" or "putative uncharacterized proteins" of unknown function. The predicted functionalities included cyclins, kinases, surface antigens, transcriptional regulators and various functions related to DNA replication, repair and cell division. CONCLUSIONS: The results of our analysis demonstrate the power of our subnetwork alignment approach to assign functionality to previously unannotated proteins. Here, the focus was on proteins involved in cell cycle regulation. These proteins are involved in the control of diverse aspects of the parasite lifecycle and of important aspects of pathogenesis.

Python as a federation tool for GENESIS 3.0.

The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be 'glued' together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models. Employed in this way, the stand-alone software components of the GENESIS 3.0 simulator provide a framework for progressive federated software development in computational neuroscience.